Bi-Level Optimization-Based Bidding Strategy for Energy Storage Using Two-Stage Stochastic Programming

Kui Hua (), Qingshan Xu, Lele Fang and Xin Xu
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Kui Hua: School of Electrical Engineering, Southeast University, Nanjing 210096, China
Qingshan Xu: School of Electrical Engineering, Southeast University, Nanjing 210096, China
Lele Fang: School of Electrical Engineering, Southeast University, Nanjing 210096, China
Xin Xu: School of Electrical Engineering, Southeast University, Nanjing 210096, China

Energies, 2025, vol. 18, issue 16, 1-22

Abstract: Energy storage will play an important role in the new power system with a high penetration of renewable energy due to its flexibility. Large-scale energy storage can participate in electricity market clearing, and knowing how to make more profits through bidding strategies in various types of electricity markets is crucial for encouraging its market participation. This paper considers differentiated bidding parameters for energy storage in a two-stage market with wind power integration, and transforms the market clearing process, which is represented by a two-stage bi-level model, into a single-level model using Karush–Kuhn–Tucker conditions. Nonlinear terms are addressed using binary expansion and the big-M method to facilitate the model solution. Numerical verification is conducted on the modified IEEE RTS-24 and 118-bus systems. The results show that compared to bidding as a price-taker and with marginal cost, the proposed mothod can bring a 16.73% and 13.02% increase in total market revenue, respectively. The case studies of systems with different scales verify the effectiveness and scalability of the proposed method.

Keywords: energy storage; market clearing; bi-level model; bidding strategy (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2025
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